Luca Ambrogioni
16 papers · 2017–2025 · 5 conferences · across top CS/AI conferences
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Conferences
AISTATS (4)
ICLR (4)
NIPS (4)
ICML (3)
UAI (1)
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Keywords
variational inference
(4)
probabilistic programming
(2)
causal inference
(2)
bayesian inference
(2)
gaussian process regression
(2)
brain connectivity
(1)
bayesian model
(1)
stochastic gradient descent
(1)
signal processing
(1)
spike train analysis
(1)
deep learning
(1)
gaussian process
(1)
likelihood-free inference
(1)
fourier transform
(1)
spectral analysis
(1)
indian buffet process
(1)
optimal transport
(1)
beta process
(1)
bayesian nonparametrics
(1)
wasserstein distance
(1)
Papers
Dynamic Negative Guidance of Diffusion Models
ICLR 2025
VCT: Training Consistency Models with Variational Noise Coupling
ICML 2025
Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
ICLR 2025
Stationarity without mean reversion in improper Gaussian processes
ICML 2024
Deterministic training of generative autoencoders using invertible layers
ICLR 2023
Spontaneous symmetry breaking in generative diffusion models
NIPS 2023
Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling
ICLR 2022
Automatic variational inference with cascading flows
ICML 2021
Automatic structured variational inference
AISTATS 2021
The Indian Chefs Process
UAI 2020
GAIT-prop: A biologically plausible learning rule derived from backpropagation of error
NIPS 2020
SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity
AISTATS 2019
Forward Amortized Inference for Likelihood-Free Variational Marginalization
AISTATS 2019
Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis
AISTATS 2018
Wasserstein Variational Inference
NIPS 2018
GP CaKe: Effective brain connectivity with causal kernels
NIPS 2017